Identifying geographic features from query prefixes

ABSTRACT

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for identifying geographic features. In one aspect, a method includes receiving a query. Geographic features are identified, each geographic feature being associated with one or more names, each geographic feature being associated with at least one name that includes the query. A feature-query score is computed for each geographic feature, including: for each name of the geographic feature that includes the query, identifying a computed feature-name score, wherein the feature-name score is computed based on a count of a number of occurrences of the name in a query log, wherein each occurrence is attributed to the feature; and computing the feature-query score based on the identified feature-name scores. The geographic features are ranked according to the feature-query scores.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit under 35 U.S.C. §119(e) of U.S.Patent Application No. 61/440,827, entitled “IDENTIFYING GEOGRAPHICFEATURES FROM QUERY PREFIXES,” filed Feb. 8, 2011, which is incorporatedherein by reference in its entirety.

BACKGROUND

This specification relates to digital information processing and, inparticular, to identifying geographic features from query prefixes.

Interactive geographic maps can be viewed in web browsers and othersoftware. A user can view an interactive geographic map for a desiredlocation which can include information pertaining to surroundingbusinesses, business addresses, contact information, and drivingdirections, for example. Some interactive maps allow users to manipulatethe maps to view adjacent sections, zoom in or out, or view satelliteimages of their desired location.

Interactive mapping systems may provide potential results in response toreceived queries. Potential results may be provided as a user types eachletter of the query, rather than after the entire query has beensubmitted.

SUMMARY

In general, one innovative aspect of the subject matter described inthis specification can be embodied in methods that include the actionsof receiving a query. Geographic features are identified, eachgeographic feature being associated with one or more names, eachgeographic feature being associated with at least one name that includesthe query. A feature-query score is computed for each geographicfeature, including: for each name of the geographic feature thatincludes the query, identifying a computed feature-name score, whereinthe feature-name score is computed based on a count of a number ofoccurrences of the name in a query log, wherein each occurrence isattributed to the feature; and computing the feature-query score basedon the identified feature-name scores. The geographic features areranked according to the feature-query scores. Other embodiments of thisaspect include corresponding systems, apparatus, and computer programs,configured to perform the actions of the methods, encoded on computerstorage devices.

These and other embodiments can each optionally include one or more ofthe following features. The actions further include providing one ormore potential results using the names of the geographic featuresordered by the ranking of the geographic features. The actions furtherinclude receiving indication of a selected potential result; andproviding map data corresponding to the selected potential result.Computing a feature score includes: for each name of the geographicfeature, computing a feature-name score using the query log; andcomputing the feature score based on the feature-name scores. Computinga feature-name score includes: dividing a number of counts of the nameattributed to the geographic feature by a total number of counts of thename in the query log. Each geographic feature is associated with aprominence score, and wherein dividing the number of counts of the nameattributed to the geographic feature by a number of counts of the namecomprises dividing the geographic feature's prominence score by the sumof prominence scores for all geographic features being associate withthe name. The query log includes, for each query in the log, informationdescribing what geographic feature a user selected after submitting thequery; and the number of counts of the name attributed to the geographicfeature is the number of times that the name occurs in the query logwith queries having information describing that the geographic featurewas selected. The query log includes, for each query in the log,information describing what geographic feature was provided to a user inresponse to the query; and the number of counts of the name attributedto the geographic feature is the number of times that the selected nameoccurs in the query log with queries having information describing thatthe geographic feature was provided. Computing the feature score basedon the feature-name scores includes selecting a maximum feature-namescore from the feature-name scores.

Particular embodiments of the subject matter described in thisspecification can be implemented so as to realize one or more of thefollowing advantages. Geographic features can be identified from queryprefixes. By using query logs, geographic features can be identifiedthat are more likely of interest to a user submitting a query prefix.Potential results and expanded potential results can be provided inconnection with an interactive mapping system based on geographicfeatures rather identified from query prefixes. Users' time can be savedin finding geographic features. Users can discover geographic features,e.g., features they may not have expected to find.

The details of one or more embodiments of the subject matter describedin this specification are set forth in the accompanying drawings and thedescription below. Other features, aspects, and advantages of thesubject matter will become apparent from the description, the drawings,and the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a diagram of an example graphical user interface for aninteractive mapping system.

FIG. 2 is a schematic diagram an example interactive mapping system.

FIG. 3 is a flow diagram of an example technique for ranking features.

FIG. 4 is a flow diagram of an example technique for providing potentialresults.

Like reference numbers and designations in the various drawings indicatelike elements.

DETAILED DESCRIPTION

FIG. 1 is a diagram of an example graphical user interface 100 for aninteractive mapping system. Users of the system can search for map databy submitting queries. In response to received queries, an interactiveview mapping system provides map data in the form of map images.

A user of the interactive mapping system can enter a query 110 into aquery box 105. By clicking a “search maps” button 120, for example, theinteractive mapping system can retrieve map data 140 and present the mapdata 140 in a viewport 130. The viewport defines a range of current mapcoordinates to be displayed on a client device.

The interactive mapping system can also provide potential results, suchas potential results 112, 113, 114, 115, and 116. A potential result canbe a name of a geographic feature that, when selected by a user, causesthe interactive mapping system to display the geographic feature in theviewport 130, e.g., instead of performing a search for the potentialresult. In some implementations, a potential result is a potentialcompleted query based on characters that the user has already entered,e.g., typed or spoken. For example, suggestion 113 (“New York”)corresponds to a potential completed query (“New York”) based on thequery 110 that has already been typed (“new y”). Multiple potentialcompleted queries are possible for any partial query. Other potentialresults are possible, including those described below.

The interactive mapping system can provide potential results as a userenters characters of a query, e.g., updating the potential results aftereach character. This is useful, for example, to disambiguate a query asa user enters the query. By looking at the potential results, the usercan determine whether selecting one will cause the viewport to display avery different location or zoom in to location already shown.

The interactive mapping system can also provide expanded potentialresults. For example, in FIG. 1, the interactive mapping systemidentified “MoMA New York” (“MoMA is an abbreviation for “Museum ofModern Art”) as an expanded potential result 112. This expandedpotential result was provided because the suggestion is likely to berelevant to users searching for “New York,” even though “MoMA” was notcontained in the query 110. In other words, while potential results 113,114, 115, 116 can be queries that a user may have eventually typed,expanded potential result 112 is provided as a relevant suggestion eventhough, based on the partial query 110, the user could not haveeventually typed “MoMA New York.”

In some implementations, expanded potential results are related to theoriginal queries in certain ways. For example, an expanded potentialresult may be a name of a geographic feature contained within a regionwhose name was identified by the original query or a potential completedquery. For example, the Museum of Modern Art in New York City iscontained within a region (“New York City”) with a name matching thepotential completed query “New York.” As a result, “MoMA New York” issuggested for the partial original query “new y.”

In some implementations, a potential result can be related to theoriginal query because the potential result is associated with ageographic feature having a name related to the original query, eventhough the potential result is not within a region whose name wasidentified by the original query or a potential completed query. Forexample, potential result 116 (“New York New York Hotel, Las Vegas, NV”)refers to a hotel in Las Vegas having a name similar to “New York” butlocated far from the city or state of New York. In this example, thesystem does not determine that “new y” refers to New York; instead, itidentifies “New York New York Hotel” as a prominent business listinghaving a name that begins with “new y.”

FIG. 2 is a schematic diagram of an example interactive mapping system210. The interactive mapping system 210 can provide map data relevant tosubmitted queries as can be implemented in an internet, an intranet, oranother client and server environment. The interactive mapping system210 is an example of an information retrieval system in which thesystems, components, and techniques described below can be implemented.

A user 202 can interact with the interactive mapping system 210 througha client device 204, e.g., a personal computer, a smart phone, or atablet computer. For example, the client 204 can be a computer coupledto the interactive mapping system through a local area network (LAN) orwide area network (WAN), e.g., the Internet. The client device 204 willgenerally include a random access memory (RAM) 206 and a processor 208.

A user 202 can submit a query 212 to a mapping engine 230 within aninteractive mapping system 210. When the user 202 submits a query 212,the query 212 is transmitted through a network to the interactivemapping system 210. The interactive mapping system 210 can beimplemented as, for example, computer programs running on one or moredata processing apparatus (e.g., computers) in one or more locationsthat are coupled to each other through a network. The interactivemapping system 210 includes a mapping engine 230. The interactivemapping system 210 responds to the query 212 by generating map results214, which are transmitted through the network to the client device 204in a form that can be presented to the user 202 (e.g., as an interactivemapping system web page to be displayed in a web browser running on theclient device 204).

The interactive mapping system 210 also provides potential results 216,which are also transmitted through the network to the client device 204.Potential results 216 can include expanded potential results, which maycontain terms that were not indicated by the original query.

When the query 212 is received by the interactive mapping system 210,the mapping 230 identifies map results 214 that correspond to the query212. Map results can be retrieved from a corpus of map data 232. The mapdata 232 can be stored in various data structures, e.g., directed graphsand tries. An indexing engine 230 can index the potentially multiplenames of features contained in the corpus of map data 232.

The interactive mapping system 210 stores information relating togeographic features, including feature names and related information, ina features database 236. A geographic feature is any place, entity,object or structure, or the like that is associated with a geographiclocation or region. Example features include countries, cities,mountains, regions, neighborhoods, streets, roads, bridges, buildings,lakes, parks, airports, and so on. Features can also include specificlocations such as businesses, landmarks, points of interest, subwaystops, and bus stops. Features can be associated with categories andsubcategories, e.g., “hotels,” “cheap hotels,” “restaurants,” “bestrestaurants,” “doctors,” and so on. Other features and feature names arepossible.

Feature names and related information can be stored in various datastructures. Table 1 illustrates an example features database includingtwo features.

TABLE 1 Feature ID Feature Names Prominence feature1 name, nother 0.1feature2 name 0.2

Each row in table 1 represents an entry for a feature having a featureID, one or more feature names, and a prominence score. A feature ID is,for example, a number or a string of characters that uniquely identifiesa feature. A feature name is, for example, a name by which users referto the feature (e.g., “New York,” “New York City,” and “NYC”). Aprominence score is a number, for example on a scale of 0-1, thatindicates the prominence of a feature. In general, a prominence score isrelated to the a-priori probability that a user would be interested in afeature, given that the user has not entered anything yet. Thus, aprominence score is independent of the name the user will use to referto that feature. For example, a feature that is searched for more often(e.g., as indicated by query logs 234, discussed below) can be moreprominent than a feature that is searched for less often. Various typesof prominence scores can be used. A prominence score is not necessarilybased on query log data. For example, a prominence score can be based onthe number of people who live in a location of a feature, the number ofpeople who visit a feature during a period of time, the number of timesthat a feature is referenced in a corpus of documents, and so on.

The interactive mapping system stores received queries in query logs234. The query logs can be parsed by the indexing engine 220 todetermine queries frequently submitted by users. The query log data canbe anonymized before it is stored or used so that personallyidentifiable data is removed. For example, a user's identity may beanonymized so that no personally identifiable information can bedetermined for the user, and the data, if compromised, cannot beassociated with a particular user or user identifier. The query log datacan be aggregated so that queries are counted without being associatedwith users or user devices. Table 2 illustrates an example query logincluding two queries.

TABLE 2 Query Count name  9 nother 12

Each row in table 2 represents a query and information about how oftenthe query was submitted. The query column lists the queries “name” and“nother,” which are also names associated with example features intable 1. The count column provides the number of times that each queryhas been submitted (e.g., over a period of time). Thus “name” has beensubmitted 9 times and “nother” has been submitted 12 times.

FIG. 3 is a flow diagram of an example technique 300 for rankingfeatures. In some implementations, the technique 300 is performed by asystem of one or more data processing apparatus. For purposes ofillustration, the technique 300 will be described with respect to asystem that performs the technique 300.

The system receives a query prefix (step 302). A query prefix is one ormore characters. For example, the query prefix can be one or morecharacters entered by a user into a client device and transmitted to aninteractive mapping system. Although the technique 300 is described fora received query prefix, more generally, the system can use any query orpart of query. For example, consider a query where a user deletes a partof a query from a word in the middle, e.g., resulting in “Guanta BayCuba.” The system can use, e.g., “guanta” as the query prefix in thefollowing steps.

The system identifies features (step 304). Each feature is associatedwith one or more names and optionally a prominence score and otherinformation. In some implementations, the system identifies features byselecting all features in a features database. In some implementations,the system identifies features by selecting features that are associatedwith names that include the query prefix or begin with the query prefix.For example, consider the query prefix “n” and the example featuresdatabase illustrated by table 1. Each of the features has a name thatstarts with “n” so each feature can be an identified feature.

The system selects a feature (step 306). For example, the system canselect features from the identified features in alphabetical order, orin order of feature IDs, or randomly. Typically, the system selectsfeatures in order of a rank of some other measure that maximizes thechances of returning relevant suggestions. For example, the system canselect features in order of prominence scores. The system selects a name(step 308). For example, the system can select names in alphabeticalorder, in an order defined by a feature database, or randomly.

The system computes a score for the selected feature given the selectedname (step 310). The score can be referred to as a feature-name score.The score is indicative of the probability that a user who submits theselected name as a query is searching for the selected feature. Forexample, consider the feature of New York City and the name “New York.”A user who submits the name “New York” as a query to an interactivemapping system could be searching for the feature New York City or otherfeatures, e.g., New York state or a hotel in Las Vegas. The score forthe feature New York City given the name “New York” is indicative of theprobability that a user who submits “New York” as a query is actuallysearching for the feature New York City. The score can also depend onthe user. For example, if the system determines that a user isassociated with a certain language, the system can adjust scores forfeatures of regions where the language is commonly spoken.

In some implementations, the system computes the score P(feature|name)using a query log (e.g., query logs 234 of FIG. 2 and the example querylog illustrated by table 2). The system can use the following equations:P(feature|name)=(counts of name attributed to feature)/(counts of name).

In this equation, “feature” refers to the selected feature, and “name”refers to the selected name. The other items in parentheses refer toinformation that is based on a query log. Each item will be described indetail in the following paragraphs, and then example computations willbe shown.

“Counts of name” refers to the number of times that the selected nameoccurs in the query log. Because the query log typically includes arecord of submitted queries for a period of time, the number of timesthat the selected name occurs in the log typically reflects the numberof submitted queries for the period of time; however, some queries cancontain the same name twice, e.g., “new york new york.”

“Counts of name attributed to feature” refers to the number of timesthat the selected name occurs in the query log and is attributed to theselected feature. The system can attribute occurrences of the name inthe query log to the feature in various ways. For example, in someimplementations, the query log includes information describing whatfeature a user ultimately selected after submitting a query, or whatfeature the system ultimately provided to the user in response to thequery.

The system can provide different features in response to the same querywhen the query is submitted under different circumstances, e.g., by adifferent user, at a different time, or by the same user from adifferent location. For example, when a user's client device isdisplaying a viewport (e.g., the viewport 130 of FIG. 1) of a certaingeographic region, the system can provide features within thatgeographic region. The system can attribute a query to the feature thatwas ultimately selected by or provided to the user.

In another example, the system can attribute occurrences of the name inthe query log to the feature using prominence scores. The system canattribute occurrences of the name in the query log using an assumptionthat a feature with a higher prominence score should be attributed tomore occurrences of the name than a feature with a lower prominencescore. For instance, the system can attribute an occurrence of the nameacross all features having the name in proportion to the prominencescores of those features. If the features have the same prominencescores, for example, the system attributes the occurrence of the nameevenly across the features. If one feature has a much higher prominencescore, the system attributes the occurrence mostly (or all) to thatfeature.

To illustrate use of the equation, consider an example scenario wherethe system receives the query prefix “n” and uses the example featurelog illustrated by table 1 and the example query log illustrated bytable 2. The system can compute P(feature|name) using the prominencescores by dividing the prominence of the selected feature by the sum ofthe prominence scores for all features associated with the selectedname. This is one example way to attribute occurrences of names in thequery log to features. The results of these computations are shown intable 3.

TABLE 3 Computation Result P(feature1|“name”) 0.1/(0.1 + 0.2) * 9/(9 +12) 0.14 P(feature1|“nother”) 0.1/0.1 * 12/(9 + 12) 0.57P(feature2|“name”) 0.2/(0.1 + 0.2) * 9/(9 + 12) 0.29

Table 3 shows the results of computing scores for both features,feature1 and feature2, and for both names associated with feature1,“name” and “nother.” The system computes these scores by repeating thesteps of selecting features and names as described further below.

The system determines whether there are more names associated with thefeature (step 312), and if so, selects another name (return to step308). For example, the system may determine whether there are more namesassociated with the feature that include the query prefix. By selectingnames associated with the feature, the system computes scores for thefeature given each associated name.

The system computes a score for the feature based on the scores giventhe names (step 314). The score can be referred to as a feature-queryscore. For example, system can use the following equations:P(feature|prefix)=P(name|prefix)*P(feature|name),whereP(name|prefix)=(counts of name)/(counts of prefix).

In these equations, “feature” refers to the selected feature, and “name”refers to the selected name, and “prefix” refers to the received queryprefix; “counts of name” refers to the same quantities described abovewith respect to step 310. The system uses P(feature|name) as describedabove with respect to step 310. “Counts of prefix” refers to the numberof names in the query log that begin with the received query prefix. Forexample, consider the query prefix “n” and the example query logillustrated in table 2. The names “name” and “nother” both begin withthe query prefix “n,” and “name” occurred 9 times and “nother” occurred12 times. So the counts of prefix for that log would be the sum of thoseoccurrences, 21.

Because multiple names can be associated with a feature, multiple valuesfor P(feature|prefix) can be computed. The final score for the featurebased on the scores can be, for example, the largest score for all ofthe names associated with the feature, the average score of the namesassociated with the feature, a weighted combination of the scores of thenames associated with the feature, and so on. In general, the finalscore can be any function of the scores of the names associated with thefeature.

To illustrate these equations, consider the example scenario describedabove with respect to step 310 and resulting in the scores shown intable 3. The system can compute the score for feature1 for the prefix“n” as max(P(feature1|“name”), P(feature1|“nother”))=0.57. The systemcan compute the score for feature2 for the prefix “n” asP(feature2|“name”)=0.29.

The system determines whether there are more identified features (step316), and if so, selects another feature (return to step 306). Byselecting various identified features, the system computes scores foreach feature.

The system ranks the identified features according to their scores asdetermined in step 314 (step 318). For example, the system can rank theidentified features in the order of their scores. The resulting rankingreflects which features are likely to be response to a user typing thequery prefix. The ranking can be used for various purposes, for example,for providing potential results.

In some implementations, the system counts entries in the query log todetermine the above counts using n-grams of a portion of the queryinstead of the full query. For example, the system can count entries for“Gary Danko” even though the query is “Gary Danko Restaurant.” This isuseful, for example, to find multiple names in one query. In someimplementations, the system counts spelling variations when countingentries in the query log. For example, the system can count entries inthe query log for “restuarant” for the query “restaurant.”

FIG. 4 is a flow diagram of an example technique 400 for providingpotential results. In some implementations, the technique 400 isperformed by a system of one or more data processing apparatus. Forpurposes of illustration, the technique 400 will be described withrespect to a system that performs the technique 400.

The system receives a query prefix (step 402). The system identifiesfeatures (step 404). The system ranks the features (step 406). Thesystem can rank the features as described above with respect to FIG. 3.

The system provides potential results using the features in the order ofthe ranking (step 408). For example, the system typically provides afirst potential result from the top ranked feature and then a secondpotential result from the next ranked feature. Each potential result canbe, for example, a name for the feature designed as the most common name(e.g., because it occurs more frequently in a query log). The system canthe provide additional potential results from additions features and,optionally, go back to the top of the ranking to provide a potentialresult that is another name associated with the top ranked feature. Thisis useful, for example, to increase the diversity of features suggestedfor a given query.

In another example, the system can provide as the top potential resultsall of the names associated with the top ranked feature, or all of thenames associated with the top ranked feature that begin with the queryprefix. The system can then provide all of the names associated with thenext ranked feature, and continue until a maximum number of potentialresults is reached.

Embodiments of the subject matter and the operations described in thisspecification can be implemented in digital electronic circuitry, or incomputer software, firmware, or hardware, including the structuresdisclosed in this specification and their structural equivalents, or incombinations of one or more of them. Embodiments of the subject matterdescribed in this specification can be implemented as one or morecomputer programs, i.e., one or more modules of computer programinstructions, encoded on computer storage medium for execution by, or tocontrol the operation of, data processing apparatus. Alternatively or inaddition, the program instructions can be encoded on anartificially-generated propagated signal, e.g., a machine-generatedelectrical, optical, or electromagnetic signal, that is generated toencode information for transmission to suitable receiver apparatus forexecution by a data processing apparatus. A computer storage medium canbe, or be included in, a computer-readable storage device, acomputer-readable storage substrate, a random or serial access memoryarray or device, or a combination of one or more of them. Moreover,while a computer storage medium is not a propagated signal, a computerstorage medium can be a source or destination of computer programinstructions encoded in an artificially-generated propagated signal. Thecomputer storage medium can also be, or be included in, one or moreseparate physical components or media (e.g., multiple CDs, disks, orother storage devices).

The operations described in this specification can be implemented asoperations performed by a data processing apparatus on data stored onone or more computer-readable storage devices or received from othersources.

The term “data processing apparatus” encompasses all kinds of apparatus,devices, and machines for processing data, including by way of example aprogrammable processor, a computer, a system on a chip, or multipleones, or combinations, of the foregoing. The apparatus can includespecial purpose logic circuitry, e.g., an FPGA (field programmable gatearray) or an ASIC (application-specific integrated circuit). Theapparatus can also include, in addition to hardware, code that createsan execution environment for the computer program in question, e.g.,code that constitutes processor firmware, a protocol stack, a databasemanagement system, an operating system, a cross-platform runtimeenvironment, a virtual machine, or a combination of one or more of them.The apparatus and execution environment can realize various differentcomputing model infrastructures, such as web services, distributedcomputing and grid computing infrastructures.

A computer program (also known as a program, software, softwareapplication, script, or code) can be written in any form of programminglanguage, including compiled or interpreted languages, declarative orprocedural languages, and it can be deployed in any form, including as astand-alone program or as a module, component, subroutine, object, orother unit suitable for use in a computing environment. A computerprogram may, but need not, correspond to a file in a file system. Aprogram can be stored in a portion of a file that holds other programsor data (e.g., one or more scripts stored in a markup languagedocument), in a single file dedicated to the program in question, or inmultiple coordinated files (e.g., files that store one or more modules,sub-programs, or portions of code). A computer program can be deployedto be executed on one computer or on multiple computers that are locatedat one site or distributed across multiple sites and interconnected by acommunication network.

The processes and logic flows described in this specification can beperformed by one or more programmable processors executing one or morecomputer programs to perform actions by operating on input data andgenerating output. The processes and logic flows can also be performedby, and apparatus can also be implemented as, special purpose logiccircuitry, e.g., an FPGA (field programmable gate array) or an ASIC(application-specific integrated circuit).

Processors suitable for the execution of a computer program include, byway of example, both general and special purpose microprocessors, andany one or more processors of any kind of digital computer. Generally, aprocessor will receive instructions and data from a read-only memory ora random access memory or both. The essential elements of a computer area processor for performing actions in accordance with instructions andone or more memory devices for storing instructions and data. Generally,a computer will also include, or be operatively coupled to receive datafrom or transfer data to, or both, one or more mass storage devices forstoring data, e.g., magnetic, magneto-optical disks, or optical disks.However, a computer need not have such devices. Moreover, a computer canbe embedded in another device, e.g., a mobile telephone, a personaldigital assistant (PDA), a mobile audio or video player, a game console,a Global Positioning System (GPS) receiver, or a portable storage device(e.g., a universal serial bus (USB) flash drive), to name just a few.Devices suitable for storing computer program instructions and datainclude all forms of non-volatile memory, media and memory devices,including by way of example semiconductor memory devices, e.g., EPROM,EEPROM, and flash memory devices; magnetic disks, e.g., internal harddisks or removable disks; magneto-optical disks; and CD-ROM and DVD-ROMdisks. The processor and the memory can be supplemented by, orincorporated in, special purpose logic circuitry.

To provide for interaction with a user, embodiments of the subjectmatter described in this specification can be implemented on a computerhaving a display device, e.g., a CRT (cathode ray tube) or LCD (liquidcrystal display) monitor, for displaying information to the user and akeyboard and a pointing device, e.g., a mouse or a trackball, by whichthe user can provide input to the computer. Other kinds of devices canbe used to provide for interaction with a user as well; for example,feedback provided to the user can be any form of sensory feedback, e.g.,visual feedback, auditory feedback, or tactile feedback; and input fromthe user can be received in any form, including acoustic, speech, ortactile input. In addition, a computer can interact with a user bysending documents to and receiving documents from a device that is usedby the user; for example, by sending web pages to a web browser on auser's client device in response to requests received from the webbrowser.

Embodiments of the subject matter described in this specification can beimplemented in a computing system that includes a back-end component,e.g., as a data server, or that includes a middleware component, e.g.,an application server, or that includes a front-end component, e.g., aclient computer having a graphical user interface or a Web browserthrough which a user can interact with an implementation of the subjectmatter described in this specification, or any combination of one ormore such back-end, middleware, or front-end components. The componentsof the system can be interconnected by any form or medium of digitaldata communication, e.g., a communication network. Examples ofcommunication networks include a local area network (“LAN”) and a widearea network (“WAN”), an inter-network (e.g., the Internet), andpeer-to-peer networks (e.g., ad hoc peer-to-peer networks).

The computing system can include clients and servers. A client andserver are generally remote from each other and typically interactthrough a communication network. The relationship of client and serverarises by virtue of computer programs running on the respectivecomputers and having a client-server relationship to each other. In someembodiments, a server transmits data (e.g., an HTML page) to a clientdevice (e.g., for purposes of displaying data to and receiving userinput from a user interacting with the client device). Data generated atthe client device (e.g., a result of the user interaction) can bereceived from the client device at the server.

While this specification contains many specific implementation details,these should not be construed as limitations on the scope of anyinventions or of what may be claimed, but rather as descriptions offeatures specific to particular embodiments of particular inventions.Certain features that are described in this specification in the contextof separate embodiments can also be implemented in combination in asingle embodiment. Conversely, various features that are described inthe context of a single embodiment can also be implemented in multipleembodiments separately or in any suitable subcombination. Moreover,although features may be described above as acting in certaincombinations and even initially claimed as such, one or more featuresfrom a claimed combination can in some cases be excised from thecombination, and the claimed combination may be directed to asubcombination or variation of a subcombination.

Similarly, while operations are depicted in the drawings in a particularorder, this should not be understood as requiring that such operationsbe performed in the particular order shown or in sequential order, orthat all illustrated operations be performed, to achieve desirableresults. In certain circumstances, multitasking and parallel processingmay be advantageous. Moreover, the separation of various systemcomponents in the embodiments described above should not be understoodas requiring such separation in all embodiments, and it should beunderstood that the described program components and systems cangenerally be integrated together in a single software product orpackaged into multiple software products.

Thus, particular embodiments of the subject matter have been described.Other embodiments are within the scope of the following claims. In somecases, the actions recited in the claims can be performed in a differentorder and still achieve desirable results. In addition, the processesdepicted in the accompanying figures do not necessarily require theparticular order shown, or sequential order, to achieve desirableresults. In certain implementations, multitasking and parallelprocessing may be advantageous.

What is claimed is:
 1. A method executed by one or more processors, themethod comprising: receiving a query; identifying a plurality ofgeographic features, each geographic feature being associated with oneor more names, each geographic feature being associated with a pluralityof names that include the query, each geographic feature beingassociated with a prominence score; computing a feature-query score foreach geographic feature, including: for each name of the geographicfeature that includes the query, computing a feature-name score,including: attributing a number of occurrences in a query log of thename in the query to the geographic feature; counting the number ofoccurrences attributed to the geographic feature; and computing thefeature-name score based on a first score and a second score, the firstscore being proportional to a number of counts of the name attributed tothe geographic feature and inversely proportional to a total number ofcounts of the name in the query log, the second score being proportionalto the geographic feature's prominence score and inversely proportionalto an aggregate of prominence scores for all geographic features beingassociated with the name; and computing the feature-query score based onthe identified feature-name scores; and ranking the geographic featuresaccording the feature-query scores.
 2. The method of claim 1, furthercomprising providing one or more potential results using the names ofthe geographic features ordered by the ranking of the geographicfeatures.
 3. The method of claim 2, further comprising: receivingindication of a selected potential result; and providing map datacorresponding to the selected potential result.
 4. The method of claim1, wherein: the query log includes, for each query in the log,information describing what geographic feature a user selected aftersubmitting the query; and the number of counts of the name attributed tothe geographic feature is the number of times that the name occurs inthe query log with queries having information describing that thegeographic feature was selected.
 5. The method of claim 1, wherein: thequery log includes, for each query in the log, information describingwhat geographic feature was provided to a user in response to the query;and the number of counts of the name attributed to the geographicfeature is the number of times that the selected name occurs in thequery log with queries having information describing that the geographicfeature was provided.
 6. The method of claim 1, wherein computing thefeature-query score based on the feature-name scores includes selectinga maximum feature-name score from the feature-name scores.
 7. A systemcomprising one or more processors configured to execute operationscomprising: receiving a query; identifying a plurality of geographicfeatures, each geographic feature being associated with one or morenames, each geographic feature being associated with a plurality ofnames that include the query, each geographic feature being associatedwith a prominence score; computing a feature-query score for eachgeographic feature, including: for each name of the geographic featurethat includes the query, computing a feature-name score, including:attributing a number of occurrences in a query log of the name in thequery to the geographic feature; counting the number of occurrencesattributed to the geographic feature; and computing the feature-namescore based on a first score and a second score, the first score beingproportional to a number of counts of the name attributed to thegeographic feature and inversely proportional to a total number ofcounts of the name in the query log, the second score being proportionalto the geographic feature's prominence score and inversely proportionalto an aggregate of prominence scores for all geographic features beingassociated with the name; computing the feature-query score based on theidentified feature-name scores; and ranking the geographic featuresaccording the feature-query scores.
 8. The system of claim 7, theoperations further comprising providing one or more potential resultsusing the names of the geographic features ordered by the ranking of thegeographic features.
 9. The system of claim 8, the operations furthercomprising: receiving indication of a selected potential result; andproviding map data corresponding to the selected potential result. 10.The system of claim 7, wherein: the query log includes, for each queryin the log, information describing what geographic feature a userselected after submitting the query; and the number of counts of thename attributed to the geographic feature is the number of times thatthe name occurs in the query log with queries having informationdescribing that the geographic feature was selected.
 11. The system ofclaim 7, wherein: the query log includes, for each query in the log,information describing what geographic feature was provided to a user inresponse to the query; and the number of counts of the name attributedto the geographic feature is the number of times that the selected nameoccurs in the query log with queries having information describing thatthe geographic feature was provided.
 12. The system of claim 7, whereincomputing the feature-query score based on the feature-name scoresincludes selecting a maximum feature-name score from the feature-namescores.
 13. A non-transitory computer storage medium encoded with acomputer program, the program comprising instructions that when executedby one or more computers cause the one or more computers to performoperations comprising: receiving a query; identifying a plurality ofgeographic features, each geographic feature being associated with oneor more names, each geographic feature being associated with a pluralityof names that include the query, each geographic feature beingassociated with a prominence score; computing a feature-query score foreach geographic feature, including: for each name of the geographicfeature that includes the query, computing a feature-name score,including: attributing a number of occurrences in a query log of thename in the query to the geographic feature; counting the number ofoccurrences attributed to the geographic feature; and computing thefeature-name score based on a first score and a second score, the firstscore being proportional to a number of counts of the name attributed tothe geographic feature and inversely proportional to a total number ofcounts of the name in the query log, the second score being proportionalto the geographic feature's prominence score and inversely proportionalto an aggregate of prominence scores for all geographic features beingassociated with the name; and computing the feature-query score based onthe identified feature-name scores; and ranking the geographic featuresaccording the feature-query scores.
 14. The computer storage medium ofclaim 13, the operations further comprising providing one or morepotential results using the names of the geographic features ordered bythe ranking of the geographic features.
 15. The computer storage mediumof claim 14, the operations further comprising: receiving indication ofa selected potential result; and providing map data corresponding to theselected potential result.
 16. The computer storage medium of claim 13,wherein: the query log includes, for each query in the log, informationdescribing what geographic feature a user selected after submitting thequery; and the number of counts of the name attributed to the geographicfeature is the number of times that the name occurs in the query logwith queries having information describing that the geographic featurewas selected.
 17. The computer storage medium of claim 13, wherein: thequery log includes, for each query in the log, information describingwhat geographic feature was provided to a user in response to the query;and the number of counts of the name attributed to the geographicfeature is the number of times that the selected name occurs in thequery log with queries having information describing that the geographicfeature was provided.
 18. The computer storage medium of claim 13,wherein computing the feature-query score based on the feature-namescores includes selecting a maximum feature-name score from thefeature-name scores.